Predictive Modelling for Incremental Cold Flow Forming: An integrated framework for fundamental understanding and process optimisation
增量冷流成型的预测建模:用于基本理解和流程优化的集成框架
基本信息
- 批准号:EP/T008415/1
- 负责人:
- 金额:$ 157.15万
- 依托单位:
- 依托单位国家:英国
- 项目类别:Research Grant
- 财政年份:2020
- 资助国家:英国
- 起止时间:2020 至 无数据
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Incremental cold flow forming (ICFF) is a metal forming process for the production of high-quality, rotationally-symmetric, hollow engineering components as widely utilised by the aerospace, automotive and oil & gas sectors. In ICFF, a cylindrical preform is attached to a rotating mandrel and axially-translating rollers apply compression to the outer surface. This leads to extrusion of the workpiece material via significant plastic deformation. As a result of the incremental process - rollers are in contact with a small area of the exterior surface of the workpiece at any one time - the extrusion of the material occurs with significantly lower force than required for conventional forming processes. ICFF is thus well suited to high-strength, hard-to-deform materials. The process is "cold" as a coolant is applied where contact occurs between the workpiece and the roller. The deformation occurs significantly below the material's recrystallisation temperature. As a result, cold work hardening occurs leading to increased strength, stiffness and hardness of the final product. A significant advantage of ICFF over conventional forging and deep drawing is the flexibility it gives engineers to design complex components of varying size. ICFF can result in considerable cost savings via improved yields, reduced production times and improved material properties, as compared to standard manufacturing routes. Furthermore, ICFF allows for rapid prototyping to support virtual product design, thereby reducing development cost and driving innovation.Despite the significant advantages that ICFF has over conventional methods, considerable challenges remain. These must be overcome prior to its widespread adoption. Foremost is the unsatisfactory repeatability and reliability of the process; it can be unstable and failure of the material can occur. Controlling the complex ICFF process is challenging. This is compounded by the large number of process parameters and the highly nonlinear nature of the deformation. Critically, there is currently no accurate and robust model to elucidate the fundamental physical mechanisms that occur during ICFF. Without such a model, the application of ICFF to new products and materials will require costly trial-and-error component-scale testing and remain an art as opposed to a science. The primary aim of this collaborative research proposal between the Advanced Forming Research Centre (AFRC) and the Glasgow Computational Engineering Centre (GCEC) is to develop an engineering design framework to model ICFF. Understanding the response of materials to the loading regime imposed by ICFF is a key component of the model development. To this end, we will undertake a detailed materials characterisation study at the AFRC. The loading on the workpiece will be measured using a highly-instrumented, research-dedicated ICFF machine. In addition, a materials characterisation procedure for ICFF will be developed that will allow industry to test new materials for ICFF thereby reducing the need for costly ICFF trials.The computational model will build upon and significantly extend the existing framework provided by MoFEM - a state-of-the-art, general purpose finite element library developed within the GCEC. The model will account for all key features of ICFF, including significant deformations, contact between rotating parts, thermal effects and residual stresses. The highly non-linear and coupled nature of these processes makes modelling challenging. The modular nature of MoFEM allows us to focus on designing new, efficient and robust numerical methods for ICFF rather than developing the core of the library. The ability of the model to accurately simulate a range of ICFF applications will be demonstrated using component scale testing conducted at the AFRC. Finally the predictive capabilities of the model will be assessed by numerically optimising the process parameters to achieve a desired net shape.
渐进式冷流成形 (ICFF) 是一种金属成形工艺,用于生产高质量、旋转对称、空心工程部件,广泛应用于航空航天、汽车和石油天然气领域。在 ICFF 中,圆柱形预成型件固定在旋转心轴上,轴向平移滚轮对外表面施加压力。这导致工件材料通过显着的塑性变形而被挤压。由于增量工艺的结果 - 辊子在任何时候都与工件外表面的一小部分区域接触 - 材料的挤出力比传统成型工艺所需的力小得多。因此,ICFF 非常适合高强度、难变形的材料。该过程是“冷”的,因为在工件和滚轮之间发生接触的地方施加冷却剂。变形发生的温度明显低于材料的再结晶温度。结果,发生冷加工硬化,导致最终产品的强度、刚度和硬度增加。与传统锻造和拉深相比,ICFF 的一个显着优势是它为工程师提供了设计不同尺寸的复杂部件的灵活性。与标准制造路线相比,ICFF 可以通过提高产量、缩短生产时间和改善材料性能来节省大量成本。此外,ICFF 允许快速原型制作以支持虚拟产品设计,从而降低开发成本并推动创新。尽管 ICFF 相对于传统方法具有显着优势,但仍然存在相当大的挑战。在广泛采用之前必须克服这些问题。首先是工艺的重复性和可靠性不令人满意;它可能不稳定并且可能发生材料失效。控制复杂的 ICFF 流程具有挑战性。大量的工艺参数和变形的高度非线性性质使情况变得更加复杂。至关重要的是,目前还没有准确且稳健的模型来阐明 ICFF 期间发生的基本物理机制。如果没有这样的模型,ICFF 在新产品和材料中的应用将需要昂贵的试错组件规模测试,并且仍然是一门艺术而不是一门科学。先进成形研究中心 (AFRC) 和格拉斯哥计算工程中心 (GCEC) 之间这项合作研究计划的主要目的是开发一个工程设计框架来模拟 ICFF。了解材料对 ICFF 施加的加载方式的响应是模型开发的关键组成部分。为此,我们将在 AFRC 进行详细的材料特性研究。工件上的负载将使用仪器仪表齐全、专用于研究的 ICFF 机器进行测量。此外,还将开发ICFF的材料表征程序,使业界能够测试ICFF的新材料,从而减少昂贵的ICFF试验的需要。计算模型将建立在MoFEM提供的现有框架的基础上,并显着扩展MoFEM——GCEC内开发的最先进的通用有限元库。该模型将考虑 ICFF 的所有关键特征,包括显着变形、旋转部件之间的接触、热效应和残余应力。这些过程的高度非线性和耦合性质使得建模具有挑战性。 MoFEM 的模块化特性使我们能够专注于为 ICFF 设计新的、高效的、鲁棒的数值方法,而不是开发库的核心。该模型准确模拟一系列 ICFF 应用的能力将通过 AFRC 进行的组件规模测试得到证明。最后,将通过数值优化工艺参数以实现所需的净形状来评估模型的预测能力。
项目成果
期刊论文数量(2)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Multifield finite strain plasticity: Theory and numerics
多场有限应变塑性:理论和数值
- DOI:10.1016/j.cma.2023.116101
- 发表时间:2023
- 期刊:
- 影响因子:7.2
- 作者:Lewandowski K
- 通讯作者:Lewandowski K
The role of shear dynamics in biofilm formation.
剪切动力学在生物膜形成中的作用。
- DOI:10.1038/s41522-022-00300-4
- 发表时间:2022-04-29
- 期刊:
- 影响因子:9.2
- 作者:Tsagkari, Erifyli;Connelly, Stephanie;Liu, Zhaowei;McBride, Andrew;Sloan, William T.
- 通讯作者:Sloan, William T.
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Chris Pearce其他文献
An Architecture for Flexibly Interleaving Planning and Execution
灵活交错规划和执行的架构
- DOI:
- 发表时间:
2015 - 期刊:
- 影响因子:0
- 作者:
Yu Bai;Chris Pearce - 通讯作者:
Chris Pearce
Convolutional Neural Networks and the Analysis of Cancer Imagery
- DOI:
- 发表时间:
2017 - 期刊:
- 影响因子:0
- 作者:
Chris Pearce - 通讯作者:
Chris Pearce
Variations on a Theory of Problem Solving
问题解决理论的变体
- DOI:
- 发表时间:
2016 - 期刊:
- 影响因子:0
- 作者:
P. Langley;Chris Pearce;Yunru Bai;Charlotte Worsfold;Mike Barley - 通讯作者:
Mike Barley
Sequoia Sourcing - Deriving a Technology Strategy
- DOI:
10.1016/s1474-6670(17)36859-3 - 发表时间:
2000-09-01 - 期刊:
- 影响因子:
- 作者:
Chris Pearce - 通讯作者:
Chris Pearce
Chris Pearce的其他文献
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{{ truncateString('Chris Pearce', 18)}}的其他基金
University of Glasgow ESRC IAA 2023 - 2028
格拉斯哥大学 ESRC IAA 2023 - 2028
- 批准号:
ES/X004414/1 - 财政年份:2023
- 资助金额:
$ 157.15万 - 项目类别:
Research Grant
University of Glasgow - Cross-disciplinary research for Discovery Science
格拉斯哥大学 - 发现科学的跨学科研究
- 批准号:
NE/X018296/1 - 财政年份:2022
- 资助金额:
$ 157.15万 - 项目类别:
Research Grant
BBSRC IAA University of Glasgow
BBSRC IAA 格拉斯哥大学
- 批准号:
BB/X511110/1 - 财政年份:2022
- 资助金额:
$ 157.15万 - 项目类别:
Research Grant
Strategic Support Package: Engineering of Active Materials by Multiscale/Multiphysics Computational Mechanics
战略支持包:通过多尺度/多物理计算力学进行活性材料工程
- 批准号:
EP/R008531/1 - 财政年份:2018
- 资助金额:
$ 157.15万 - 项目类别:
Research Grant
Mathematic modelling and computational methods in solid mechanics
固体力学数学建模与计算方法
- 批准号:
EP/E504876/1 - 财政年份:2007
- 资助金额:
$ 157.15万 - 项目类别:
Training Grant
Computational homogenisation for modelling heterogeneous multi-phase materials
用于建模异质多相材料的计算均质化
- 批准号:
EP/D500273/1 - 财政年份:2006
- 资助金额:
$ 157.15万 - 项目类别:
Research Grant
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